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Procedure for denoising dual-axis swallowing accelerometry signals

a technology of accelerometry and accelerometer, which is applied in the field of denoising dual-axis swallowing accelerometry signals, can solve the problems of high computational complexity, inability to produce optimal results for signals that are not smooth, and inherently noisy measurements, and achieves low computational complexity and small reconstruction errors

Inactive Publication Date: 2015-03-31
HOLLAND BLOORVIEW KIDS REHABILITATION HOSPITAL
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0007]This invention teaches a method for denoising of long duration dual-axis swallowing accelerometry signals using a computationally efficient algorithm. The algorithm achieves low computational complexity by performing a search for the optimal threshold in a reduced wavelet subspace. To find this reduced subspace, the proposed scheme uses the minimum value of the estimated reconstruction error. By finding this value, the proposed approach also achieves a smaller reconstruction error than previous approaches such as MNDL. SURE-based and Donoho's approaches. This finding has been confirmed for both, synthetic test signals and dual-axis swallowing accelerometry signals.

Problems solved by technology

Nevertheless, such measurements are inherently very noisy due to various physiological and motion artifacts.
However, wavelet denoising with the suggested optimal threshold does not necessarily produce the optimal results for signals that are not smooth. i.e., signals with noiseless coefficients being of very small amplitude for a large number of basis functions.
Recent attempts to overcome this shortcoming have yielded methods that can suffer from high computational complexities for very long signals, and do not necessarily reach the optimal results.

Method used

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  • Procedure for denoising dual-axis swallowing accelerometry signals
  • Procedure for denoising dual-axis swallowing accelerometry signals

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Methodology of the Invention

[0012]Consider N noisy discrete-time observations:

x(n)=f(n)+ε(n)  (1)

where n=0, . . . , N−1, f(n) is a sampled version of a noiseless continuous signal, and ε(n) is the additive white Gaussian noise drawn from N (0, σε2)

[0013]Assume that f(n) can be expanded using

basis functions, bk(n), on the observation space, BN:

f(n)=Σk=1Nckbk(n)  (2)

[0014]where

ck=bk(n),f(n)  (3)

and (p,q) denotes the inner product of vectors p and q. However, given the noisy observations, the coefficients, ck, can only be approximated as follows:

ĉk=bk(n),x(n)=ck+bk(n),ε(n)  (4)

Denoising and Reconstruction Error

[0015]If f(n) can be described with M nonzero coefficients, where Mk, represent samples of a zero mean Gaussian random variable with variance σε2. A classical approach known as wavelet denoising diminishes the effects of noise by first expanding the noisy signal in terms of orthonormal bases of compactly supported wavelets. The estimated coefficients below some threshold, τ, are ...

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Abstract

Dual-axis swallowing accelerometry is an emerging tool for the assessment of dysphagia (swallowing difficulties). These signals however can be very noisy as a result of physiological and motion artifacts. A novel scheme for denoising those signals is proposed, i.e., a computationally efficient search for the optimal denoising threshold within a reduced wavelet subspace. To determine a viable subspace, the algorithm relies on the minimum value of the estimated upper bound for the reconstruction error. A numerical analysis of the proposed scheme using synthetic test signals demonstrated that the proposed scheme is computationally more efficient than minimum noiseless description length (MNDL) based de-noising. It also yields smaller reconstruction errors (i.e., higher signal-to-noise (SNR) ratio) than MNDL, SURE and Donoho denoising methods. When applied to dual-axis swallowing accelerometry signals, the proposed scheme improves the SNR values for dry, wet and wet chin tuck swallows. These results are important to the further development of medical devices based on dual-axis swallowing accelerometry signals.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]This application claims the benefit of U.S. Provisional Patent Application No. 61 / 218,976 filed on Jun. 21, 2009FIELD OF INVENTION[0002]This invention relates in general to the field of dual-axis swallowing accelerometry signal analysis and more specifically to a method for denoising such signals.BACKGROUND OF THE INVENTION[0003]Swallowing accelerometry is a potentially informative adjunct to bedside screening for dysphagia. These measurements are minimally invasive, requiring only the superficial attachment of a sensor anterior to the thyroid notch. Even though single-axis accelerometers were traditionally used for swallowing accelerometry, recent studies have shown that dual-axis accelerometers can capture more of the clinically relevant information. Nevertheless, such measurements are inherently very noisy due to various physiological and motion artifacts. Denoising of dual-axis swallowing accelerometry signals is therefore essential f...

Claims

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Application Information

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Patent Type & Authority Patents(United States)
IPC IPC(8): A61B5/103A61B5/00G06F17/18
CPCG06F17/18A61B5/4205A61B5/7203A61B5/726
Inventor CHAU, TOMSEJDIC, ERVIN
Owner HOLLAND BLOORVIEW KIDS REHABILITATION HOSPITAL
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